Determinants of capital structure of listed real estate companies in vietnam

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE HAGUE VIETNAM THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS DETERMINANTS

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES

HO CHI MINH CITY THE HAGUE

VIETNAM THE NETHERLANDS

VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

DETERMINANTS OF CAPITAL STRUCTURE

OF LISTED REAL ESTATE COMPANIES

IN VIETNAM

BY

DO QUANG THAI

MASTER OF ARTS IN DEVELOPMENT ECONOMICS

HO CHI MINH CITY, DECEMBER 2014

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES

HO CHI MINH CITY THE HAGUE

VIETNAM THE NETHERLANDS

VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

DETERMINANTS OF CAPITAL STRUCTURE

OF LISTED REAL ESTATE COMPANIES

IN VIETNAM

A thesis submitted in partial fulfilment of the requirements for the degree of

MASTER OF ARTS IN DEVELOPMENT ECONOMICS

By

DO QUANG THAI

Academic Supervisor:

NGUYEN HOANG BAO

HO CHI MINH CITY, DECEMBER 2014

ABSTRACT

This research focuses on the impact of determinants to capital structure with respect to 56 listed real estate companies in Vietnam from 2010 to 2013 Basing on two theories of trade-off and pecking order, capital structure, which is defined by debt ratio,

is expected to provide the current prospect of Vietnamese real estate sector The off theory mentioned about the establishment of optimal capital structure for enterprises, while theory of pecking order implied the financing decisions by board of managements

For the methodology, Fixed Effect Model is used to test the results of regression model Non-random statistics of Fixed Effect Model would be more efficient and consistent in order to reduce the level of bias The data set will be arranged by panel data, which combined both cross section and time series, helped to improve the significant results of regression model

Policy implications carefully mentioned about the limitation of both Pecking order and Trade-off theories in Vietnam evidence For Pecking order, board of management prefers to use external financing budgets by issuing new bonds or stocks rather than internal financing capital The abuse of debt financing is also pointed out the hard pressures on banking system, securities markets, and the corporate governance structure of the listed firms Besides that, Trade-off theory has limited its effect in Vietnam due to centrally planned economy The government needs to change its administration in some listed real estate companies to create fair environment for the whole market

TABLE OF CONTENTS

CHAPTER I: PRESENTATION OF THESIS RESEARCH……… 1

1.1 Problem Statement……… 1

1.2 Research Objectives……… 3

1.3 Research Questions……… 4

1.4 Scope of study……… 5

1.5 Structure of thesis research……… 6

CHAPTER II: LITERATURE REVIEW……… 7

2.1 Review of Empirical Studies……… 7

2.2 Hypothesis of Variables……… 11

2.2.1 Dependent Variable: Debt Ratio……… 11

2.2.2 Independent Variables……… 11

CHAPTER III: RESEARCH METHODOLOGY……… 12

3.1 Analytical Framework……… 12

3.2 Regression Model……… 16

3.2.1 Assumptions of Regression Model……… 16

3.2.2 Limitations of Regression Model……… 17

3.2.3 Equation of Regression Model……… 17

3.2.4 Data……… 18

3.2.5 Research Method……… 19

CHAPTER IV: RESULTS AND EXPLANATIONS……… 20

4.1 Overview of Real Estate Companies in Vietnam……… 20

4.2 Impacts of Vietnamese Real Estate Market……… 22

4.2.1 Inflow Capital to Real Estate Market……… 22

4.2.2 Land and Property Law……… 24

4.2.3 Urbanization in Vietnam……… 24

4.2.4 Economic growth rate (GDP’s Growth rate)……… 25

4.3 Descriptive Statistics……… 26

4.4 Leverage Testing……… 32

4.5 Results of Regression Model……… 34

4.5.1 Multicollinearity Test by Correlation Matrix……… 35

4.5.2 Using Wald-Test to Adjust Core Regression Model……… 36

4.5.3 Regression Model……… 36

4.5.4 Jarque-Bera Test for Normality (in Residuals)……… 37

4.6 Result Explanations……… 38

CHAPTER V: CONCLUSIONS……… 40

5.1 Summary of Research Methodology……… 40

5.2 Major Findings……… 41

5.3 Policy Implications……… 41

5.4 Limitations……… 42

5.5 Further Researches……… 43

REFERENCES……….44

APPENDIX……… 49

LIST OF TABLES

Table 2.1: Expected signs of five related determinants……… 14

Table 4.1: Correlation matrix of debt ratio and five related determinants… 31

Table 4.2: T-statistic of debt ratio and each of determinants……… 31

Table 4.3: Leverage test of debt ratios……… 32

Table 4.4: Results of regression model by FEM……… 34

Table 4.5: Regression model without DEBT_INTEREST……… 37

LIST OF FIGURES Figure 2.1: The Trade-off Model……… 8

Figure 2.2: The Pecking Order……… 9

Figure 3.1: Analytical framework of capital structure’s determinants……… 12

Figure 4.1: VN Index and Real Estate Index from the period 2010-2013… 21

Figure 4.2: FDI flows to Vietnam from 2006-2013……….23

Figure 4.3: Number of Urban Cities in Vietnam from 1985-2012………… 24

Figure 4.4: Vietnam GDP’s Growth Rate from 2004-2013……… 25

Figure 4.5: Descriptive Statistic of debt interest and debt ratio……… 26

Figure 4.6: Descriptive Statistic of depreciation ratio and debt ratio……… 27

Figure 4.7: Descriptive Statistic of size and debt ratio……… 28

Figure 4.8: Descriptive Statistic of profitability and debt ratio……… 29

Figure 4.9: Descriptive Statistic of volatility and debt ratio……… 30

ABBREVATION

EBITDA Earnings before interest, taxes, depreciation, and amortization

CHAPTER I: PRESENTATION OF THESIS RESEARCH

In 2014, the Vietnamese real estate market eventually has lighted up positive signs of recovery, which followed the gains of the stock market, benefits of interest rate cuts, and expansionary changes in land and property ownership laws, stimulated the market’s liquidity The first chapter involves in five parts to present the overview of thesis research They consist of problem statement, research objectives, research questions, scope of study, and general structure of the study

1.1 PROBLEM STATEMENT

The financial crisis from 2007 to 2009 in the United States were mentioned the worst crash of economic system in Wall Street since the Great Depression happened in 1930s by research of Lee, Rabanal and Sandri (January, 2010) This trauma highly contributed to the failure of key businesses, reduced the living standards, and also resulted in a slowdown of whole national production activities

It initially started with the U.S mortgage market and spread out its impact over the world as “domino effect”

Vietnamese economy now is integrated its domestic market towards worldwide Therefore, the industrial real estate market in Vietnam could not avoid

to be influenced in this twisting curse According to the study of Jehan and Luong (2008), they provided the problems of Vietnam real estate market in front of global financial crisis Their priority is given by lack of capital resources which came from credit agencies or financial institutions The function of many credit markets seriously stopped to function at all and impacted on other industries Most of local credit institutions admitted that the process took extreme constrains to provide lending credits to Small and Medium Enterprises (SMEs) The problem is described

as a downside bottleneck effect in the credit system because the tight monetary policies of governments Basing on research paper of Pham et al (August, 2013),

they clarified transparently the important contribution of SMEs to Vietnamese economy They also pointed out the policy implications to reduce the stress of bottle neck effect which may help government to restore economic growth In fact, the industrial real estate in Vietnam has experienced with the hardest landing since the last booming period of the housing marketing in 2001 Do, Zhang and Zheng (2014) demonstrated his argument of frozen liquidity in Vietnam real estate market Due to low turnover, low disbursement, and sharp fall of housing prices, there is calculated approximate $3.1 billion USD of inventories for listed real estate companies in

2012 Their statistics announced that 10,077 of local real estate enterprises had to close their business due to low trading liquidity in 2013 Ho Chi Minh and Hanoi are two largest areas which flooded in huge volume of inventories In details, Hanoi had inventories of over 6,580 apartments and Ho Chi Minh had inventories of 7,830 apartments, which were worth of 12,900 billion VND and 17,480 billion VND respectively

When the total demand unexpectedly dropped to a lower level, the companies did not know how to settle down their current debts Most of Vietnamese enterprises still are vulnerable due to not only volatility of financial market but also different economic scenarios One more reason is that most of Vietnamese enterprises are developing and limited experiences, so they may receive the prospect of default when the crisis suddenly come into them (Jehan and Luong, 2008) The main specification of the real estate market is to require a huge amount

of capital to accomplish the housing projects

To evaluate the effectiveness of capital structure in real estate sector, time lags in different economic scenarios are the most struggling obstacles which somehow lead to wrong final financial decisions The market may be immediately impacted by changes of the equity market, but it takes time to reflect on business activities Companies will fall deeper to the bottom if they do not resolve immediately the current issues by adjusting their capital structure to lower level

Vicol (2010) successfully demonstrated in his thesis research that real estate companies in the crisis scenarios would face a lot of issues relating to their own business activities such as financial cash flow, general operations, inventories, and depreciation methodology affecting their adjustments of capital structure

The author realizes that there is an abnormal phenomenon in Vietnamese enterprises related to real estate sector The high debt ratio in their financial statement alerted the risk-on to business activities when the market crashed Although facing with high interest expenses and low level of market demand, most

of real estate enterprises are willing to borrow more short-term debts in order to maintain their current business activities This strange phenomenon will be explained by hypotheses and assumptions in this study are basing on two primary theories of corporate capital structure decisions which are ranked as theories of trade-off and pecking order However, not only all of the problems came from the internal business operations, but also these potential externalities may impact on the consequences, such as monetary policies and management levels

By applying theories of the trade-off and pecking order, we expect to find down the determinants which will make any significant effect on capital structure in real estate corporations towards a specific optimal financial decision in the future

1.2 RESEARCH OBJECTIVES

First of all, this research paper tries to verify clearly the concepts and priorities of defining corporate capital structure By Trade-off and Pecking Order theories, the author wants to test the impact of both theories on each of determinants

Secondly, the author would like to start with analyzing the debt ratio during the crisis Kantor and Holdsworth (2010) showed that the leverage of firm gradually

increased in the crisis and also continued to rise sharply in post-crisis due to time lags These time lags were referred to the delay of the project construction The inefficient account receivables also determined the lack of capital or risky capital structure which owners had to borrow more debts in order to settle down these problems in the crisis stage The research by Kang, Maysami, Mensah, and Pham (2013) demonstrated that the negative operating business of real estate companies performed gloomy visions in the crisis High interest expenses just wiped out their earnings, and cash flow gradually shifted from positive sign to negative sign over this period Furthermore, Kim and Stone (1999) figured out that high levered corporations might face an unexpected cut-off of lending credits from financial institutions which was imitated obviously in their thesis Its effect of financial distress may drive the company go bankrupt The urgent response from board of directors is to divest in non-core projects and reduce goods or materials in inventory

at a discount price to survive in the market

Finally, in the modern age, there is a new trend for firms in the crisis may use spin—off strategy which may help parent company to achieve an efficient capital structure or lower debt ratio by excluding several debt amounts Basically, the spin-off strategy does not change the levered ratios in consolidated financial statement But this strategy somehow will help business to get better financial ratios

of parent company The parent company has high opportunities to be raised its credit by rating agencies There are also alternative solutions of internal financing (Nguyen, 2010) such as pre-sale system to the buyers or diversified business sector

in order to stay in the market In general, the author specifies their mechanisms by typical examples in the data set

1.3 RESEARCH QUESTIONS

What the key determinants make the significant exposures on capital structure in Vietnamese real estate enterprises which importantly need to be

answered in this study The efficient optimization will be an answer for those real estate enterprises which are struggling with debt and interest coverage in different business prospects

In general, the optimal level will follow the industrial benchmarks of different stages of economy Basing on previous theories of trade-off and pecking order, there can be several questions, which concern the choice of capital structure, are tested by statistics and regression model The writer mentions them in three assumptions: firstly, the debt leverage of one company adjusts to go down gradually during the current crisis Secondly, real estate companies will struggle with less financial budget by debt issuers Finally, the relationship between debt and profitability is expected to perform a divergent trend This would help writer to analyze and evaluate Vietnamese listed real estate corporations with respect to capital structure

There are 56 observations in the data set They are listed real estate companies in Vietnamese stock market The primary data, including balance sheet, income statement and cash flow statement are collected from State Securities Commission (SSC) The survey period is limited from 2010 to 2013

1.5 STRUCTURE OF THESIS RESEARCH

The thesis research consists of five chapters: presentation, literature review, research methodology, results and explanations, and conclusions In details, chapter

I will mention briefly about an overview of this study, research objectives, research questions, and scope of the study Next, chapter II will discuss about literature review of pecking order and trade-off theories from previous studies Chapter III will be an essential part of this study to demonstrate analytical framework, research methodology, data collection and introduction of determinants In the next part, chapter IV is the section to consider about results and explanations of regression model testing the statistical significance between FEM and REM Finally, chapter V

is the last part to mention about conclusions of this study Major findings and limitations also imply directly to improve the results of further researches

CHAPTER II: LITERATURE REVIEW

This chapter will present the principal of Modigliani and Miller, pecking order, and trade-off theories Each of theories evaluates the different purposes of capital structure related to financial decisions of company There are two parts in this chapter Firstly, the empirical studies review the efficiencies of previous papers Secondly, hypothesis of variables will explain their specific impacts on capital structure

2.1 REVIEW OF EMPIRICAL STUDIES

Modigliani and Miller (1958), two famous foundations of corporate finance, clearly explained the concept of capital structure needed to be generated the great interests among financial researchers The general idea of their theorem mentioned that a levered company enjoyed the more benefits than those companies without using leverage They stated strongly that an optimization of debt level reasonably adjusts to business values and cost of using capital In particular, the company would tentatively increase or decrease their debt levels in order to not only balance healthy capital structure but also maximize their earnings

The trade-off model presented an optimal debt level to utilize perfectly the earning interest depending on the preferential tax reduction and costs of distress occurring once the corporation faced with financial difficulties This suggestion simply changes the company’s financial decisions from the actual level of debts towards the optimal ones A business which obtains the greater investment opportunities and profitability, the more leverage methodologies they expect to use

as the definition of trade-off theory developed by two authors of Fama and French (2002) According to Modigliani and Miller (1963), totally agreed that trade-off theory would reflect the company’s ambition on debt level, and then the owner of the firm was seeking much higher levels of debt than people see in reality to

maximize their business values in the stock market In figure 2.1, a high level of debt helps the firm to increase its own value by advantages of tax shield and financial discipline At the optimal peak, the firm fails to rise in its value Bankruptcy costs may reflect the fixed costs, which owner will pay permanently while agency costs come from the interest expenses These two factors will push not only the value of firm lower, but also the debt level continues to rise

Figure 2.1: Trade-off Model

Following the previous research paper from Frank and Goyal (2005), Pecking Order hypothesis implies the simplest definition of debt ratios which typically tends to rise up once new investment opportunity dominates the current company’s risk and to fall if the gain payoff cannot offset the equivalent risk Furthermore, almost all discussions keep maintaining some versions of other special things by interpreting the relative use of internal and external funds In details, their findings suggest that the more profitable the companies wish to earn, the less levered they use for business activities It is no doubt to say that there is an absolute consistent with the Pecking Order Enterprises mostly are insensitive to change their

capital structures unless there will potentially occur unexpected crisis It explains clearly that there was a very slow adjustment speed towards an optimal level of debt In figure 2.2, Pecking Order explains different considerations from board managements They want to keep internal capital rather than raising funds budget from outside financial institutions This underlying debt has no costs and helps the owners to feel relax to decide the firm’s objectives

Figure 2.2: Pecking Order

So, this paper applies the principal theories of pecking order and trade-off, which are able to test the determinants of corporate capital structure By the way, different economic scenarios are also affecting on corporate level of debt The conflicts of effects between Trade-off and Pecking Order are distracting manager’s financing decisions In consequences, the statistic results will somehow explain the difference and efficiency in each theory Some evidences proved that the Pecking Order is the most ultimate methodology than Trade-off to change the current debt level

However, because of the differences in asset management and intervention of government policies, real estate companies may be impacted by single trade-off or pecking order theory The simultaneous presence of both theories is extremely rare

at the same period (Meng and Wang, 2012) This will make the firm struggling with interest disputes between shareholders and debt owners Therefore, the level of explanation may not prove absolutely in this crisis stage with the appearance of externalities

The specification of each determinant will imply the different impact on deficit finance or debt ratio of capital structure The writer also considers about the change of asset mobilization in real estate enterprises will make a greater effect on level of debt This would explain by huge inventories (normally hold the large proportion of capitalization) The writer also hopes that the more income the real estate companies earned, the lower debt level which was demonstrated obviously by pecking order Those companies tend to use internal capital supporting to their own business rather than external financing such as financial institutions or credit lenders

The trade-off model is expected to put the risk on business activities It means that a firm needs to accept more risks to acquire higher growth rate of business development However, the writer considers about the dynamic momentum

of real estate development in Vietnam They are more rooms to grow potentially in further decades Now they just need time to adjust optimal level of debt to keep growing and expanding their market shares Restructuring market is the prior path

to rebalance supply and demand for Vietnamese real estate sector This helps to illuminate the economic growth, and to enhance the living standards for the whole society In consequences, an increasing level of debt is inevitable trend for Vietnam real estate companies

2.2 HYPOTHESIS OF VARIABLES

To demonstrate these expected impacts, the writer considers to present regression model in next coming chapter The data is arranged by panel data which

is followed two comparative statistical models between FEM and REM Debt ratio

is dependent variable which is calculated by total liability over total asset There are five determinants to explain the different impacts on debt ratio Analytical framework will also be appeared in the initial part of the next chapter to illustrate how the regression model is working and specifications of each determinant in terms of signs (positive or negative trend)

2.2.1 Dependent Variable: Debt Ratio

Total Liability/Total Assets is the general concept of debt ratio to mention about how many percentages of assets which are built up from liability obligation

By evaluating this ratio, we can easily consider the financial health status of real estate enterprises However, the limitation of this ratio is that in case any enterprises had many large accounts of payment to suppliers, deferred revenues, tax and other payables to the State budget, etc Accordingly, this ratio will exaggerate the financial leverage of enterprises The higher total liability over the total assets shows the lower independence of equity, and as the consequence, the enterprises are struggling with financial crisis due to pressure of debt interest

the pecking order theory demonstrates that corporations would prefer the budgets which came from internal funds such as retained earnings rather than external funds from financial institutions It performs true effect of pecking order to explain the impact of profitability on debt ratio However, when the corporations are facing with financial distress and external fund needs to be supported urgently, the prior choice is to borrow debts from outside financial institutions, then possibly with the corporate bonds, and consequently with equity, such as preferential shares as a final mandate (Brealey and Myers, 1991) In contrast, the trade-off theory imply the positive trend between profitability and debt ratio by the reason “more leverage created more incomes” (Bowen et al., 1982) In this paper, the writer would like to test the earnings before interest, taxes, depreciation, and amortization (EBITDA) divided by enterprise value (EV) as an indicator of profits in business activities It seems to be more suitable than the ratio of EBIT divided by total assets due to specifications of real estate industry Most of real estate corporations may inherent some indirect assets which are under constructions or gain extra goodwill income Enterprise value absolutely provides a clearer outlook of companies than their own total assets The inverse trend between leverage and profitability would expect to change in different economic scenarios

b) Company’s Size

From the previous studies, Rajan and Zingales (1995) stated that impact of size on capital structure is ambiguous issue They claimed that a larger firm will face with low probability of bankruptcy Frank and Goyal (2003) confidentially wrote down in their thesis that an inverse movement between business scale and bankruptcy risk Their abstracts mentioned about the dilemma situation of giant holdings to consider whether they should trigger advanced level of debt or not to expand their assets They provided a conclusion of the larger firms should be more leveraged It means that a historic and reputable firm normally received a high credit rating score or low default risk evaluation and was able to attract more

attention from financial analysts and rating agencies Clearly, larger firms may issue new amount of debts with less capital costs The business scale and leverage should

be on the same movement depending on above logic In conclusion, for the relationship between size and debt ratio, the pecking order claimed the negative signs while there is positive sign of trade-off model

c) Risk of Business Activities (volatility)

The volatility from business performance is the best representative indicator

to measure the probability of risk According to trade-off model, when the standard deviation of profitability was increasing, the expected returns also tend to increase

as the normal consequences (Kester, 1986) The business risk would increase in higher level due to the volatility of earnings However, a negative relation is found

by (Bradley et al., 1984) and (Titman and Wessels, 1988) In this study, the author wants to follow Booth et al (2001)’s formula framework by calculating a periodically standard deviation in each of real estate companies The volatility of earnings before interest, taxes, depreciation, and amortization’s growth (EBITDA_GROWTH) in fiscal year basis will indicate well the risk from business performances For this determinant, the author generally puts the positive sign for the standard deviation of EBITDA_GROWTH and debt leverage to test how effective the enterprise would increase 1% of leverage to create an amount of earnings

d) Depreciation

Some previous empirical studies confirmed the theoretical prediction of trade-off model, such as Kim and Sorensen (1986) confirmed the positive relationship of depreciation and debt ratio However, a negative relation between non-debt tax shields and leverage is also found by (Huang and Song, 2002) and (Titman and Wessels, 1988) They mentioned that when an asset depreciates, its

book value also decreases by the amount of accumulated depreciation Assuming that total liabilities remained at the original level, the total liabilities over total assets ratio was moved to higher phase by the lower value of total assets In this study, the writer follows Titman and Wessels (1988)’s methodology to calculate the depreciation ratio by collecting enterprise’s depreciation in fiscal year basis, finally divided by total assets In consequences, the relationship between depreciation ratio and debt leverage performs an inverse discretion

e) Debt Interest

Normally, the costs of financial divisions come from interest expenses Zhang and Li (2008) revealed that higher interest expenses will stimulate the debt leverage Basing on trade-off theory, they demonstrated the evidence that interest expenses became a tax shield to reduce the amount of taxes, and created an incentive to use the high amounts of debt eventually However, a rise of interest expense will also unexpectedly argue the conflict between debt holders to equity holders, and the shareholders to managers The positive significance of these determinants to debt ratio will be likely to expect in regression model

Indicators Brief definition Expected signs

Profitability EBITDA divided by EV (+)Trade-off

(-)Pecking Order

Company’s Size Natural Logarithm of

Total Assets

(+)Trade-off (-)Pecking Order

Volatility Standard deviation of

EBITDA

(+)Trade-off (-)Pecking Order

Depreciation ratio Depreciation divided by

total assets

(+)Trade-off (-)Trade-off

Debt Interest Natural Logarithm of

Interest Expenses (+)Trade-off

Table 2.1: Expected signs of five related determinants

CHAPTER III: RESEARCH METHODOLOGY

From previous studies, the writer points out five determinants which have different effects on capital structure Debt ratio will be presented for dependent variable in regression model There are two main parts in this chapter They are analytical framework and introduction of the regression model The analytical framework reviews the impact of independent variables on debt ratio while regression model describes the model’s shape, method of data collection and research statistic

3.1 ANALYTICAL FRAMEWORK

Figure 3.1: Analytical framework of capital structure’s determinants

As shown in figure 3.1, the framework analyses the consequence of cause and effect that may provide ultimately the relationship results In the graph, internalities and externalities are two main factors which cause the greatest effect on capital structure As the writer mentioned in previous parts, the externalities of government policies and management levels should not test in this paper due to lack

of information For the internal determinants, there are five factors such as size, profitability, volatility, depreciation ratio, and debt interest costs that may give the

clear impact to debt ratio Basing on historic researches of authors, they typically concluded the different signs of each factor towards debt ratio

3.2 REGRESSION MODEL

3.2.1 Assumptions of Regression Model

a) The first assumption is that the writer will use five determinants which have an impact on debt ratio If one company are seeking new amount of inflow capital by borrowing from credit issuers, the creditor will carefully consider about the current debt ratio of the firm Almost Vietnamese real estate corporations have depended heavily on capital lending from commercial banks or financial credit issuers

b) The next assumption will be the relationships between debt ratio and each

of independent variables Xi which are linear in the parameters of the specific functional form chosen (basing on descriptive statistics) Furthermore, the writer also uses the quadratic term to check whether the nonlinear relationship between debt ratio and each of independent variables happened in the regression model By completing the square of each determinant and adding them to statistical equation, the writer received no significant improvement of squared determinants to regression model

c) Fixed Effect Model (FEM) and Random Effect Model (REM) are comparative statistical methodologies which will be used in this regression model The test of Hausman will choose the best response to put in the regression model

3.2.2 Limitations of Regression Model

a) In regression model, the writer only discusses on internal determinants The external determinants of government policies and management skills are ambiguous information and the lack of data They are determined by social preferences and business development respectively The effect of externalities will

be explained more in part of the conclusions

b) Some outliers seem to be quite influential in the data set If these observations made any significant changes in result, we would like to use dummy data points for regression model

c) Data set is short duration (from 2010 to 2013) So, it would not perform well the status of observation due to time lags

3.2.3 Equation of Regression Model

𝑫𝒆𝒃𝒕𝒓𝒂𝒕𝒊𝒐 = 𝜷𝟎 + 𝜷𝟏𝑿𝟏 + 𝜷𝟐𝑿𝟐 + ⋯ + 𝜷5𝑿5 + 𝜺

Where: - Debt ratio is calculated by total liability over total asset

- 𝑋1, 𝑋2, 𝑋3, X4, and X5 are presented by depreciation ratio, size, debt interest, profitability, and volatility respectively

- 𝛽1, 𝛽2, 𝛽3, 𝛽4, and 𝛽5 are coefficients of each determinant

Chi Minh Stock Exchange (HSX) and Hanoi Stock Exchange (HNX) The main standard of those selected companies is that their market capitalizations must be over 100 billion VND Some of them are diversified in many real estate sub-sectors, including consultant, supplier, contractor, etc In this paper, the author uses descriptive statistics to observe the current debt ratio in Vietnamese listed real estate companies The comparative statistical models of FEM and REM will provide the effect of five determinants to changes in debt ratio The data set will design as dated panel data, which identify company’s names as cross section series and years as date series

This paper focuses on the period of time from 2010 to 2013 when Vietnamese

real estate market just slightly passed over the bottom of crisis At this stage, the

bubble of real estate industry seems to be predictably triggered by tight monetary policies in order to reduce the hike rates of inflation, and to stabilize the macroeconomics The cutting credit for the real estate market causes a negative impact on real estate companies The prices of land, housing, and office lease had declined significantly to the lowest level, which most of investors forced to sell-off about 50% from their original values, compared to the past gorgeous period The failure of price equilibrium between sellers and buyers in this process also leaded to the low trading liquidity, bankruptcy, and high unemployment rate in real estate sector

3.2.5 Research Method

Descriptive statistics presents the brief summaries of observations in data set

The descriptive graphs also mention about the dispersion or central tendency of observations The Regression line will point out the relationship between debt ratio and its determinants The author bases on result of this test to confirm the shape of regression model The matrix correlation also presents to test the multicolineary of related determinants in regression model

Leverage testing provides a general analysis of determinants volatility

Mean, median, and standard deviation are three main indicators in this statistic The time period will base on the data set The purpose of leverage testing is to know the average debt ratio of industrial real estate We compare some top holdings with healthy capital structures Hence, we may apply the benchmark of this ratio (optimal capital structure) for the Vietnamese market

Linear regression will help to explain the impact of explanatory variables

(depreciation ratio, size, debt interest, profitability, and volatility) on dependent variable (debt ratio) Depending on the research of Song (2005), he clearly proved that debt ratio is an important concept to define and understand obviously the financial risk in capital structure The risk from financial operations will challenge a corporation to settle down all liability obligations for short, medium and long term prospects of business campaign

Since 2008, most of real estate companies’ profits in Vietnam are disrupted

by financial obligations with the escalating interest coverage ratio and debt ratios The model is structured by panel data The advantage of panel data is mentioned clearly by Baltagi (1995) that heterogeneity bounds to individuals, companies, nationalities, etc The specifications of panel data regression model will take heterogeneity explicitly by allowing for individual –specific variables

CHAPTER IV: RESULTS AND EXPLANATIONS

There are six parts in this chapter Two first parts review the scale of listed real estate companies in Vietnamese stock exchanges and historic development of real estate sectors in Vietnam Next three parts perform the result and testing of regression model Final part concludes some general opinion about significant level

of model

4.1 OVERVIEW OF REAL ESTATE COMPANIES IN VIETNAM

Vietnamese real estate market shows a quite discrete density in terms of quality and quantity In 2013, there are around 60 real estate companies listing on Vietnamese stock market and their market capitalizations estimate 125 thousand billions, an averaging contribution of 10% in the whole market In top leading companies, Vingroup (VIC) and Hoang Anh Gia Lai (HAG) seems to dominate other domestic competitors basing on enormous incomes and revenue sales in year basis Most of real estate projects are locally focusing in Hanoi, Ho Chi Minh, and few of frontier cities

The specifications of real estate companies depend on two main elements: huge amount of capital and sufficient land property The entry barrier of real estate market stays at normal level in comparison to banking or oil and gas industries It means that Vietnamese real estate enterprises potentially have more rooms to develop in further prospect In real estate market, enterprises mostly dominate against other competitors by land locations and numbers of land ownership Those two factors will present the vision of each real estate company when board of directors set up the pro-forma financial projections

Since 1990, Vietnamese real estate market has endured three times of frozen liquidity and three times of price booming The recent booming of real estate

market recorded in 2007 to 2008 when a huge amount of FDI rushed into Vietnam economy However, after this historic glory, the decline of housing demand reflected on the slump of real estate market The figure 4.1 has performed the downtrend of real estate index which suffered losses of 60-70% of its original level since 2010 One more important specification of real estate companies is deferred revenues, which came from the investor’s account to invest the current real estate projects In central phase of crisis, this amount will be lower than the pre - crisis period due to most of the investors feel lack of confidence to put more their capitals into real estate enterprises In fact, as long as the crisis has remained in economy, the real estate corporations try to escape out the market share by selling off their goods with a large proportion in price

Figure 4.1: The comparison of VN Index and Real Estate Index from the period

2010-2013 Data: Vietstock

4.2 IMPACTS OF VIETNAMESE REAL ESTATE MARKET

The development of real estate sector in Vietnam is much more depending

on lending capitals (credit agencies and foreign direct investment), urbanization, land and property ownership law, and growth rate of economy

4.2.1 Inflow Capital to Real Estate Market

Credit Agencies provides lending capital to enterprises through by financial

services The main specification of real estate sector is to require a large investment

capital at the initial stage for various purposes, such as site clearing costs, construction costs, and labor costs, etc Therefore, real estate companies always

need sufficient budgets from credit institutions to fulfill their projects

Basing on high debt ratio, the operating activities of real estate enterprises mostly are impacted by lending interest rate and monetary policies from State Bank

of Vietnam (SBV) As the theory of macroeconomics, high interest rate would reduce the incentives of investment

Foreign Direct Investment (FDI) will improve the economic development by

investing to urban infrastructure, securities, or joint venture Moreover, the capitals

of FDI will create more jobs to Vietnamese labor force and reduce the unemployment rate Vietnam had a stable politics and applied interesting regulations to attract foreigners in recent years Since 2006, Vietnam officially became a member of World Trade Organization (WTO), which remarked completely an important stage of integrated economy In the age of globalization, FDI is increasingly playing an important role to country’s development Specifically, in figure 4.2, FDI established a record of inflow registration capital to Vietnamese market, up to 70 billion USD in 2008 Although the economy had to

struggle with global financial crisis, Vietnam maintained to attract over 15 billion USD of FDI’s registration on year basis from 2010-2013

Figure 4.2: FDI flows to Vietnam from 2006-2013 Data: World Bank

For developing countries, the relationship between FDI and debt ratio is also considered in this thesis First and foremost, FDI may come from the international credit institutions which provide preferential capitals to domestic enterprises It is called a transferred capital from developed countries to developing countries in order to seek more benefits Secondly, the local real estate companies can issue international convertible bonds to attract more FDI’s capitals Although their debt ratio will increase, they can avoid the conflict of diluted earnings per share to current shareholders Finally, to those debt ratios, which are mostly structured by international capitals, may face with a rise in debt interest costs due to the risk of exchange rates

FDI flows to Vietnam from 2006-2013

4.2.2 Land and Property Law

According to Resolution 19 publishing in 2009 and validating until 2013, the current land and property ownership law is limited the foreigner’s abilities to buy permanently a house or land in Vietnam To stimulate the domestic real estate market, the authorities recently reduced the tax rates of commercial house projections, and approve the new law to expand the requirements of owning land and property for foreigners in Vietnam This windfall somehow boosts the higher investments on Vietnamese real estate sector

4.2.3 Urbanization in Vietnam

According to World Bank’s The 2014 Revision, Vietnam is one of the top countries which had fastest speed of urbanization in South East Asia countries The number of cities was rising sharply year by year It is an essential step of modern industrial revolution in Vietnam

Figure 4.3: Number of Urban Cities in Vietnam from 1985-2012 Data: United

Nations Human Settlements Programme

0 5 10 15 20 25 30

Number of Urban Cities in Vietnam from 1985-2012

However, the fast speed of urbanization also requires the quality of urban infrastructure and control of housing construction This makes a positive impact on potential growth for Vietnam real estate companies More urban cities appears, more demand of housings, commercial trade centers, entertainments, etc will also move to higher levels

4.2.4 Economic growth rate (GDP’s Growth Rate)

The economic growth rate shows the close relationship with development of real estate sector When the economy is boosting, the demand of leasing offices, commercial trade centers will rise to catch up this convergent trend Moreover, a person, which has higher income, requires diversified luxury products instead of normal products This phenomenon also generates quickly the sale revenues for real estate companies

Figure 4.4: Vietnam GDP’s Growth Rate from 2004-2013 Data: World Bank

4.3 DESCRIPTIVE STATISTICS

 Relationship between Debt ratio and Debt Interest

Figure 4.5: Descriptive Statistic of debt interest and debt ratio

The coefficient of determination, R-squared linear is equal to 0.791 says that 79.1% of the variation in debt interest (Y) is explained well by the linear relation with debt ratio (X) This leaves 20.9% of the variation in debt interest left to be explained by other factors (except X) This result measures the strong relation of two variables: debt ratio and debt interest by least-squares regression line

There are some companies, which are supported preferential capitals from credit lenders, have small amount of debt interest Petro Vietnam Premier Recreation JSC (HNX: PVR) is one of subsidiaries of Petro Vietnam Although PVR’s debt ratio maintained at level of 50%, but its debt interest is approximately equal to zero

-4 -3 -2 -1 0 1 2 3 4

 Relationship between Debt ratio and Depreciation Ratio

Figure 4.6: Descriptive Statistic of depreciation ratio and debt ratio

In this graph, the result of R-squared linear is equal to 0.795 says that 79.5%

of the variation in depreciation ratio (Y) is explained well by the linear relation with debt ratio (X) This leaves 20.5% of the variation in depreciation ratio left to be explained by other factors (except X) This result also measures the strong relation

of two variables: debt ratio and depreciation ratio (X:Y)

However, Tan Binh Import Export JSC (HSX: TIX) had the highest points

of depreciation ratio which its scatter plot identified at (0.58:0.36), (0.44:0.43), and (0.42:0.44), while Sonadezi Long Thanh (HSX: SZL)’s depreciation ratios were located at (0.53:0.18), (0.59:0.21), and (0.39:0.280 These two observations are significantly scattering far away from R-squared linear

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